- read metadata from first file in ome tiff sequence

ndbioimage/readers/tifread.py

@@ -1,3 +1,5 @@
+import re
+import warnings
 from abc import ABC
 from functools import cached_property
 from itertools import product
@@ -6,8 +8,8 @@ from pathlib import Path
 import numpy as np
 import tifffile
 import yaml
-import warnings
-from ome_types import model, from_xml
+from lfdfiles import TiffFile
+from ome_types import from_xml, model
 
 from .. import AbstractReader, try_default
 
@@ -31,48 +33,54 @@ class Reader(AbstractReader, ABC):
 
     def get_ome(self):
         if self.reader.is_ome:
-            with warnings.catch_warnings():
-                warnings.simplefilter('ignore', category=UserWarning)
-                return from_xml(self.reader.ome_metadata)
+            match = re.match(r'^(.*)(pos.*)$', self.path.stem, flags=re.IGNORECASE)
+            if match is not None and len(match.groups()) == 2:
+                a, b = match.groups()
+                file0 = TiffFile(self.path.with_stem(a + re.sub(r'\d', '0', b)))
+                with warnings.catch_warnings():
+                    warnings.simplefilter('ignore', category=UserWarning)
+                    ome = from_xml(file0.ome_metadata)
+                    ome.images = [image for image in ome.images if self.path.stem[:len(image.name)] == image.name]
+                    return ome
+
+        page = self.reader.pages[0]
+        size_y = page.imagelength
+        size_x = page.imagewidth
+        if self.p_ndim == 3:
+            size_c = page.samplesperpixel
+            size_t = self.metadata.get('frames', 1)  # // C
         else:
-            page = self.reader.pages[0]
-            size_y = page.imagelength
-            size_x = page.imagewidth
-            if self.p_ndim == 3:
-                size_c = page.samplesperpixel
-                size_t = self.metadata.get('frames', 1)  # // C
-            else:
-                size_c = self.metadata.get('channels', 1)
-                size_t = self.metadata.get('frames', 1)
-            size_z = self.metadata.get('slices', 1)
-            if 282 in page.tags and 296 in page.tags and page.tags[296].value == 1:
-                f = page.tags[282].value
-                pxsize = f[1] / f[0]
-            else:
-                pxsize = None
+            size_c = self.metadata.get('channels', 1)
+            size_t = self.metadata.get('frames', 1)
+        size_z = self.metadata.get('slices', 1)
+        if 282 in page.tags and 296 in page.tags and page.tags[296].value == 1:
+            f = page.tags[282].value
+            pxsize = f[1] / f[0]
+        else:
+            pxsize = None
 
-            dtype = page.dtype.name
-            if dtype not in ('int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32',
-                             'float', 'double', 'complex', 'double-complex', 'bit'):
-                dtype = 'float'
+        dtype = page.dtype.name
+        if dtype not in ('int8', 'int16', 'int32', 'uint8', 'uint16', 'uint32',
+                         'float', 'double', 'complex', 'double-complex', 'bit'):
+            dtype = 'float'
 
-            interval_t = self.metadata.get('interval', 0)
+        interval_t = self.metadata.get('interval', 0)
 
-            ome = model.OME()
-            ome.instruments.append(model.Instrument(id='Instrument:0'))
-            ome.instruments[0].objectives.append(model.Objective(id='Objective:0'))
-            ome.images.append(
-                model.Image(
-                    id='Image:0',
-                    pixels=model.Pixels(
-                        id='Pixels:0',
-                        size_c=size_c, size_z=size_z, size_t=size_t, size_x=size_x, size_y=size_y,
-                        dimension_order='XYCZT', type=dtype,  # type: ignore
-                        physical_size_x=pxsize, physical_size_y=pxsize),
-                    objective_settings=model.ObjectiveSettings(id='Objective:0')))
-            for c, z, t in product(range(size_c), range(size_z), range(size_t)):
-                ome.images[0].pixels.planes.append(model.Plane(the_c=c, the_z=z, the_t=t, delta_t=interval_t * t))
-            return ome
+        ome = model.OME()
+        ome.instruments.append(model.Instrument(id='Instrument:0'))
+        ome.instruments[0].objectives.append(model.Objective(id='Objective:0'))
+        ome.images.append(
+            model.Image(
+                id='Image:0',
+                pixels=model.Pixels(
+                    id='Pixels:0',
+                    size_c=size_c, size_z=size_z, size_t=size_t, size_x=size_x, size_y=size_y,
+                    dimension_order='XYCZT', type=dtype,  # type: ignore
+                    physical_size_x=pxsize, physical_size_y=pxsize),
+                objective_settings=model.ObjectiveSettings(id='Objective:0')))
+        for c, z, t in product(range(size_c), range(size_z), range(size_t)):
+            ome.images[0].pixels.planes.append(model.Plane(the_c=c, the_z=z, the_t=t, delta_t=interval_t * t))
+        return ome
 
     def open(self):
         self.reader = tifffile.TiffFile(self.path)

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ndbioimage"
-version = "2025.3.0"
+version = "2025.3.1"
 description = "Bio image reading, metadata and some affine registration."
 authors = [
     { name = "W. Pomp", email = "w.pomp@nki.nl" }